Hi all, Bjornsdotter et al. (2011) (http://dx.doi.org/10.1016/j.neuroimage.2010.07.044) used a Monte Carlo searchlight method where a non-exhaustive searchlight is performed, and each voxel is assigned the average of the the information metric for those searchlights in which it is involved. Taken to its limit, this is just a spatial smoothing of a traditional searchlight analysis.
The method for operating in the individual subject space is straightforward (construct a searchlight QueryEngine, take an average in each neighborhood), but I want to perform this in the FreeSurfer average subject (fsaverage) space. I thought I'd try this with the new SurfaceQueryEngine, but I'm not entirely sure how to train it. It looks like it wants a .nii loaded with voxels holding vertex indices, but I don't have one for fsaverage. Hopefully this is really easy and I'm just missing something, but the tutorials don't seem to be keeping pace with all the new features. :-) Thanks! -- Christopher Johnson Ph.D. Candidate, Quantitative Neuroscience Laboratory Boston University
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